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train_commands
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train_commands
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direct:
python3 train.py --dataroot /nfs/154/dataset2/shadegan/data-single/renders/ --name direct --checkpoints_dir test_checkpoints --model direct --dataset_mode direct --input_nc 1 --output_nc 1 --load_size 256 --crop_size 256 --batch_size 1 --texture /nfs/151/gpu/raghav/data/shadegan/brushes_v2 --netG unet_256
sp:
python3 train.py --dataroot /nfs/154/dataset2/shadegan/data-single/renders/ --name sp --checkpoints_dir test_checkpoints --model sp --dataset_mode sp --input_nc 1 --output_nc 1 --load_size 256 --crop_size 256 --batch_size 1 --texture /nfs/151/gpu/raghav/data/shadegan/brushes_v2 --netG unet_256
sp_ws:
python3 train.py --dataroot /nfs/154/dataset2/shadegan/data-six/renders/ --name sp_ws --checkpoints_dir test_checkpoints --model sp_ws --dataset_mode sp_ws --input_nc 1 --output_nc 1 --load_size 256 --crop_size 256 --batch_size 1 --texture /nfs/151/gpu/raghav/data/shadegan/brushes_v2 --netG unet_256
se:
python3 train.py --dataroot /nfs/154/dataset2/shadegan/data-six/renders/ --name se --checkpoints_dir test_checkpoints --model se --dataset_mode sp --input_nc 1 --output_nc 1 --load_size 256 --crop_size 256 --batch_size 1 --texture /nfs/151/gpu/raghav/data/shadegan/ --netG unet_256